llvm-project/polly
Michael Kruse 91f46bb77e [Polly] Reject reject regions entered by an indirectbr/callbr.
SplitBlockPredecessors is unable to insert an additional BasicBlock
between an indirectbr/callbr terminator and the successor blocks.
This is needed by Polly to normalize the control flow before emitting
its optimzed code.

This patches rejects regions entered by an indirectbr/callbr to not fail
later at code generation.

This fixes llvm.org/PR51964
2021-09-26 21:21:50 -05:00
..
cmake [Windows][Polly] Disable LLVMPolly module for all compilers on Windows 2020-09-15 09:12:38 +03:00
docs polly: remove the old reference to svn in the doc 2021-08-27 10:46:50 +02:00
include/polly [Polly] Reject reject regions entered by an indirectbr/callbr. 2021-09-26 21:21:50 -05:00
lib [Polly] Reject reject regions entered by an indirectbr/callbr. 2021-09-26 21:21:50 -05:00
test [Polly] Reject reject regions entered by an indirectbr/callbr. 2021-09-26 21:21:50 -05:00
tools Fix typos throughout the license files that somehow I and my reviewers 2019-01-21 09:52:34 +00:00
unittests [Polly] Don't redundantly link libPolly into unittests. 2021-08-24 03:07:30 -05:00
utils Harmonize Python shebang 2020-07-16 21:53:45 +02:00
www [Branch-Rename] Fix some links 2021-02-01 16:43:21 +05:30
.arclint
.gitattributes
.gitignore
CMakeLists.txt Remove .svn from exclude list as we moved to git 2020-10-21 16:09:21 +02:00
CREDITS.txt
LICENSE.TXT Rename top-level LICENSE.txt files to LICENSE.TXT 2021-03-10 21:26:24 -08:00
README

README

Polly - Polyhedral optimizations for LLVM
-----------------------------------------
http://polly.llvm.org/

Polly uses a mathematical representation, the polyhedral model, to represent and
transform loops and other control flow structures. Using an abstract
representation it is possible to reason about transformations in a more general
way and to use highly optimized linear programming libraries to figure out the
optimal loop structure. These transformations can be used to do constant
propagation through arrays, remove dead loop iterations, optimize loops for
cache locality, optimize arrays, apply advanced automatic parallelization, drive
vectorization, or they can be used to do software pipelining.